Optimization design of precision machine tool bed considering assembly deformation

doi:10.3785/j.issn.1006-754X.2022.00.035

Chin J Eng Design

2022, Vol. 29

Issue (3): 318-326 DOI: 10.3785/j.issn.1006-754X.2022.00.035

Optimization Design

Optimization design of precision machine tool bed considering assembly deformation

Guang-ming SUN(

),Yi-miao WANG,Qian WAN,Kun GONG,Wen-jin WANG,Jian ZHAO(

)

School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin 300384, China

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Abstract

In order to reduce the assembly deformation and improve the assembly accuracy of machine tool, an optimization design method of machine tool bed considering assembly deformation was proposed. Firstly, the assembly deformation parts of machine tool and assembly deformation mechanism of the machine tool bed were analyzed, and the factors affecting the assembly deformation of machine tool bed and their influence laws were studied; secondly, based on response surface model and genetic algorithm, a multi-objective optimization method of machine tool bed considering assembly deformation was proposed, and the optimization design process was given; finally, taking the classic machine tool bed as an example, taking the structural parameters of the bed as design variables, and taking the minimum of bed mass, assembly deformation amplitude, maximum static deformation and maximum of first-order natural frequency as the optimization objective, the optimal design of the bed was carried out. The results showed that the number and thickness of stiffener plates along the length and width of the bed had an important influence on the assembly deformation; after optimization, the assembly deformation could be effectively reduced, the assembly accuracy could be improved, and the bed mass smaller, the stiffness was bigger, and the dynamic performance was better. The research results not only provide a reference for the structural analysis and optimization design of foundation large parts of machine tool, but also provide a theoretical basis for the multi-objective optimization of other similar equipment, which has important engineering practice value.

Key words： precision machine tool assembly deformation optimization design method finite element analysis

Received: 09 March 2021 Published: 05 July 2022

CLC:

TH 122

Corresponding Authors: Jian ZHAO E-mail: gmsun@tju.edu.cn;zhaojiantcu@163.com

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Cite this article:

Guang-ming SUN,Yi-miao WANG,Qian WAN,Kun GONG,Wen-jin WANG,Jian ZHAO. Optimization design of precision machine tool bed considering assembly deformation. Chin J Eng Design, 2022, 29(3): 318-326.

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https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2022.00.035 OR https://www.zjujournals.com/gcsjxb/Y2022/V29/I3/318

考虑装配变形的精密机床床身优化设计

为了减小装配变形，提高机床装配精度，提出了一种考虑装配变形的机床床身优化设计方法。首先，分析了机床装配变形部位和床身装配变形机理，研究了影响机床床身装配变形的因素及其影响规律；其次，基于响应面模型和遗传算法，提出了考虑装配变形的机床床身多目标优化方法，给出了优化设计流程；最后，以经典的机床床身为实例，以床身结构参数为设计变量，以床身质量、装配变形幅值、最大静变形量最小和一阶固有频率最大为优化目标，对床身进行优化设计。结果表明：床身长度和宽度方向的筋板数量和筋板厚度均对装配变形有重要影响；床身优化后，可有效减小装配变形，提高装配精度，同时使床身的质量更小、刚度更大和动态性能更优。研究结果不但为机床基础大件的结构分析与优化设计提供了参考，也为其他类似设备的多目标优化提供了理论依据，具有重要的工程实践价值。

关键词： 精密机床, 装配变形, 优化设计方法, 有限元分析

Fig.1 Assembly process of machine tool

Fig.2 Deformed parts of machine tool assembly

Fig.3 Assembly position of guide rail and bed

Fig.4 Finite element model of assembly position of guide rail and bed

Fig.5 Simulation results of assembly deformation of guide rail and bed

Fig.6 Influence of the number of the bed stiffener plat on assembly deformation

Fig.7 Influence of the thickness of the bed stiffener plate on assembly deformation

Fig.8 Guide rail and bed assembly experiment

Fig.9 Experimental results of guide rail and bed assembly

Fig.10 Multi-objective optimization design flow of machine tool bed

Fig.11 Initial model of machine tool bed

Table 1 Factors and levels of orthogonal test of machine tool bed optimization

编号	试验因素					试验结果
编号	$x 1$ /条	$x 2$ /mm	$x 3$ /条	$x 4$ / mm	$x 5$ /mm	$m$ /t	δ_max/μm	H_ad/μm	$f 1$ /Hz
1	2	20	0	20	-90	1.069	5.43	19.2	485.50
2	2	25	1	25	-60	1.238	4.63	17.8	510.00
3	2	30	2	30	-30	1.462	3.53	17.8	517.00
4	2	35	3	35	0	1.738	2.50	12.7	523.36
5	2	40	4	40	30	2.066	2.14	18.4	529.20
6	3	20	1	30	0	1.294	3.49	47.3	545.75
7	3	25	2	35	30	1.557	2.79	16.1	559.17
8	3	30	3	40	-90	1.869	2.22	11.7	569.80
9	3	35	4	20	-60	1.689	2.21	10.4	586.85
10	3	40	0	25	-30	1.298	3.01	13.3	544.80
11	4	20	2	40	-60	1.625	2.57	12.9	572.87
12	4	25	3	20	-30	1.567	2.32	12.7	598.97
13	4	30	4	25	0	1.834	2.10	10.4	612.29
14	4	35	0	30	30	1.356	2.51	16.0	537.16
15	4	40	1	35	-90	1.595	2.39	12.2	677.59
16	5	20	3	25	30	1.649	2.21	17.8	599.95
17	5	25	4	30	-90	1.953	2.06	11.7	620.40
18	5	30	0	35	-60	1.385	2.37	11.9	526.67
19	5	35	1	40	-30	1.662	2.16	11.1	694.20
20	5	40	2	20	0	1.830	1.98	10.1	701.32
21	6	20	4	35	-30	2.048	2.08	13.0	615.49
22	6	25	0	40	0	1.385	2.28	10.3	510.78
23	6	30	1	20	30	1.573	2.06	14.2	655.56
24	6	35	2	25	-90	1.807	1.94	9.38	715.96
25	6	40	3	30	-60	2.081	1.88	10.2	725.48

Table 2 Result of orthogonal test of machine tool bed optimization

参数	$F m$	$F δ m a x$	$F H a d$	$F f 1$
$R 2$	0.998 6	0.998 9	0.995 8	0.989 0
$R a d j 2$	0.989 0	0.991 5	0.907 6	0.966 4

Table 3 Fitting accuracy of response surface model

Table 4 Design variables of machine tool bed before and after optimization

Fig.12 Comparison of finite element simulation analysis results of machine tool bed before and after optimization

参数	原始值	优化值	变化率/%
$m$ /t	1.56	1.16	-25.64
δ_max/μm	17.2	10.6	-38.37
H_ad/μm	0.030 2	0.025 7	-14.90
$f 1$ /Hz	559.12	662.78	18.54

Table 5 Comparison of dynamic and static characteristic parameters of machine tool bed before and after optimization


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